IoT service slicing and task offloading for edge computing
JaeYoung Hwang, Lionel Nkenyereye, NakMyoung Sung, JaeHo Kim, and, JaeSeung Song

TL;DR
This paper proposes a novel edge-based IoT service virtualization architecture that enhances latency and traffic management, demonstrating a twofold reduction in transmission time compared to traditional cloud-based solutions.
Contribution
It introduces an innovative framework for virtualization of IoT services at the edge, optimizing performance and resource management through MEC and network slicing integration.
Findings
Edge-based IoT architecture reduces transmission time by 50%.
Experimental results confirm improved latency over cloud-based platforms.
Architecture supports real-time, low-latency IoT services.
Abstract
With the advancement of IoT technology, various domains such as smart factories, smart cities and smart cars use the IoT to provide value-added services. In addition, technologies such as MEC and network slicing provide another opportunity for the IoT to support more advanced and real-time services that could not have been previously supported. However, the simple integration of such technologies into the IoT does not take full advantage of MEC and network slicing or the reduction of latency and traffic prioritization, respectively. Therefore, there is a strong need for an efficient integration mechanism for IoT platforms to maximize the benefit of using such technologies. In this article, we introduce a novel architectural framework that enables the virtualization of an IoT platform with minimum functions to support specific IoT services and host the instance in an edge node, close to…
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Taxonomy
TopicsIoT and Edge/Fog Computing · Software-Defined Networks and 5G · Advanced Computing and Algorithms
